TY - GEN
T1 - Robust asymmetric Adaboost
AU - Ormeño, Pablo
AU - Ramírez, Felipe
AU - Valle, Carlos
AU - Allende-Cid, Héctor
AU - Allende, Héctor
N1 - Funding Information:
This work was supported by the following Research Grants: Fondecyt 1110854 and FB0821 Centro Científico Tecnológico de Valparaíso. Partial support was also received from CONICYT (Chile) Ph.D. Grant 21080414.
PY - 2012
Y1 - 2012
N2 - In real world pattern recognition problems, such as computer-assisted medical diagnosis, events of a given phenomena are usually found in minority, making it necessary to build algorithms that emphasize the effect of one of the classes at training time. In this paper we propose a variation of the well-known Adaboost algorithm that is able to improve its performance by using an asymmetric and robust cost function. We assess the performance of the proposed method on two medical datasets and synthetic datasets with different levels of imbalance and compare our results against three state-of-the-art ensemble learning approaches, achieving better and comparable results.
AB - In real world pattern recognition problems, such as computer-assisted medical diagnosis, events of a given phenomena are usually found in minority, making it necessary to build algorithms that emphasize the effect of one of the classes at training time. In this paper we propose a variation of the well-known Adaboost algorithm that is able to improve its performance by using an asymmetric and robust cost function. We assess the performance of the proposed method on two medical datasets and synthetic datasets with different levels of imbalance and compare our results against three state-of-the-art ensemble learning approaches, achieving better and comparable results.
KW - adaboost
KW - asymmetric cost functions
KW - ensemble learning
KW - robust methods
UR - http://www.scopus.com/inward/record.url?scp=84865607386&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33275-3_64
DO - 10.1007/978-3-642-33275-3_64
M3 - Conference contribution
AN - SCOPUS:84865607386
SN - 9783642332746
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 519
EP - 526
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
T2 - 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Y2 - 3 September 2012 through 6 September 2012
ER -